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Senior AI Engineer (LLMs & Agentic AI)

Applaudo

Nuevo Remote
Contrat Remote Senior 🇬🇧 English
Python SQL Snowflake Anthropic OpenAI prompt engineering OAuth OIDC vector databases RAG AWS MLOps CI/CD observability Hugging Face GPU acceleration

Descripcion del puesto

About the role

Applaudo is seeking a Senior AI Engineer to design, build, and maintain production‑grade large language model (LLM) applications and agentic AI systems. You will work in a small, lightly‑managed team, making autonomous design decisions and collaborating closely with engineering leadership.

Key responsibilities

  • Build and operate MCP servers, including tool definitions, resource management, and multi‑step orchestration.
  • Integrate Anthropic and OpenAI models into production, handling prompt versioning, fallback strategies, and performance optimization.
  • Design intent classification, routing workflows, and multi‑API orchestration to resolve user intents.
  • Develop evaluation frameworks, write SQL for model monitoring, and support the chat/MCP interface backend.
  • Participate in architecture discussions and continuously improve AI systems through experimentation and best practices.

Required profile

  • Bachelor’s degree in Computer Science, AI, Data Science or equivalent professional experience.
  • Strong spoken English (B2+) for live technical discussions with US stakeholders.
  • Proven experience delivering production AI applications with Python and LLM technologies.
  • Hands‑on experience authoring and deploying MCP servers used by other users or systems.
  • Ability to work independently in a partially documented brownfield codebase.

Required skills

  • Python (async I/O, typing, schema validation, error handling, testing).
  • SQL and cloud data warehouses (Snowflake preferred).
  • LLM integration (Anthropic, OpenAI) and prompt engineering.
  • OAuth/OIDC authentication, authorization patterns.
  • Experience with vector databases, Retrieval‑Augmented Generation (RAG).
  • Familiarity with AWS services (Batch, ECS, Lambda, SQS).
  • Knowledge of MLOps practices (CI/CD, observability, reproducible pipelines).
  • Optional: Hugging Face model deployment, GPU acceleration, fine‑tuning, and open‑source model evaluation.

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Publicado hace 1 hora

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